Magnetic Energy Storage Research Articles

Optimal design and cost of superconducting magnetic energy storage for voltage sag mitigation in a real distribution network

One of the most important aspects of power quality for a distribution network's operation is the voltage sag issue. Simultaneous starting of irrigation motors fed from a distribution network leads to a voltage drop, which degrades the network's power quality. Mitigation of the voltage sag was carried out before by using superconducting magnetic energy storage (SMES) with a pre-defined capacity. The innovation of the present research work is optimal design of SMES including optimal sizing of SMES and its controller parameters with the consideration of its optimal cost for mitigating voltage sag resulting from simultaneous starting of irrigation motors in a real Egyptian distribution network. This is made by minimizing a multi-objective function formulated by a weighted-sum voltage sag and SMES cost. A new optimization technique called Mountain Gazelle Optimizer (MGO) is used to optimize the sizing of fuzzy logic controller (FLC)-SMES as well as the weight factors of multi-objective function. These factors are not free for the decision maker to choose. An actual Egyptian electric distribution network named Karot feeding 16 induction-driven irrigation motors and residential loads, is implemented as a test case study to exhibit the performance of the suggested optimal FLC-SMES strategy in mitigating the voltage sag. For validating the performance of the MGO technique, the obtained results are compared with those determined by particle swarm optimization (PSO). The present results show that the MGO-optimized SMES unit with a capacity of 0.135 MJ and actual cost of 0.2483 M$ successfully mitigated the voltage-sag in the investigated network due to simultaneous starting of the irrigation motors where the voltage never drops below 0.9 p.u. against 0.625 MJ capacity and 0.6934 M$ actual cost for the non-optimized SMES. This corresponds to about 78 % and 64 % reduction in capacity and actual cost of the SMES unit.

A novel low voltage ride-through scheme for DFIG based on the cooperation of hybrid energy storage system and crowbar circuit

To improve the low voltage ride-through (LVRT) capability of DFIG, a novel LVRT scheme based on the cooperation of hybrid energy storage system (HESS) and crowbar circuit is proposed. The HESS composed of superconducting magnetic energy storage (SMES) and batteries is connected in the DC-link bus of DFIG. During grid faults, the HESS is switched to stabilize the DC-link bus voltage of DFIG, the grid-side converter (GSC) of DFIG is switched to inject reactive power to the grid for improving the grid fault voltage and the crowbar circuit is activated in real-time to avoid RSC from being damaging according to the rotor current. During normal operation, the HESS is controlled to deal with power difference between the turbine generation power and power dispatching command, and the GSC of DFIG is controlled to manage the output power of the DFIG with HESS. Finally, the simulations of the DFIG with HESS system is conducted in RTDS platform, and the simulation results show that the proposed scheme can effectively achieve the LVRT of DFIG during gird faults and flexibly manage the DFIG output power with HESS during normal operation.

New Cascaded 1+PII2D/FOPID Load Frequency Controller for Modern Power Grids including Superconducting Magnetic Energy Storage and Renewable Energy

Having continuous decrease in inertia and being sensitive to load/generation variation are considered crucial challenging problems for modern power grids. The main cause of these problems is the increased penetration capacities of renewables. An unbalanced load with generation power largely affects grids’ frequency and voltage profiles. Load frequency control (LFC) mechanisms are extensively presented to solve these problems. In the literature, LFC methods are still lacking in dealing with system uncertainty, parameter variation, structure changes, and/or disturbance rejection. Therefore, this paper proposes an improved LFC methodology using the hybrid one plus proportional integral double-integral derivative (1+PII2D) cascaded with fractional order proportional-integral-derivative (FOPID), namely, the proposed 1+PII2D/FOPID controller. The contribution of superconducting magnetic energy storage devices (SMES) is considered in the proposed design, also considering hybrid high-voltage DC and AC transmission lines (hybrid HVDC/HVAC). An optimized design of proposed 1+PII2D/FOPID controller is proposed using a new application of the recently presented powerful artificial rabbits optimizers (ARO) algorithm. Various performance comparisons, system changes, parameter uncertainties, and load/generation profiles and changes are considered in the proposed case study. The results proved superior regulation of frequency using proposed 1+PII2D/FOPID control and the ARO optimum parameters.

Analysis of Magnetic Nonpotentiality in the Flaring Active Region NOAA 12887

Solar flares are explosive events resulting from the release of stored magnetic energy in active regions. In this study, the Spaceweather Helioseismic and Magnetic Imager Active Region Patch (SHARP) data is utilized to extract nonpotential magnetic parameters of the NOAA 12887 active region, which produced an X1.0 class flare in October 2021. The analysis revealed that the electric current became non-neutral and unstable before the X-class flare due to an increase in the shear angle, exceeding 90 degrees through a collision of positive and negative polarities. We also assessed the magnetic nonpotentiality parameters, including free energy, vertical current, current helicity, and current neutrality. At the beginning, the parameters exhibited elevated values, reflecting the complex nature of the active region. Subsequently, it became even more complex following the collision event. Flare Ribbons and filaments were also observed by the AIA/SDO 1600 Å and 304Å images on this phase. However, the overall complexity decreased over time, with temporary increases after the collision event and subsequent flares. The development of new complex areas outside the collision zone had a lesser impact on the parameter values. The current neutrality value increased after the collision, implying an increasingly unstable region, but sharply decreased after the X-class flare, indicating a return to a more stable state for the active region.

Application of inertia emulation control strategy with energy storage system in multi-area hydro -thermal system using a novel metaheuristic optimized tilt controller

This article presents the application of a novel artificial hummingbirds’ algorithm (AHA) based tilt-integral second order of double-derivative controller (TIDD2) in a three-area hydro-thermal power system. Also, the inertia emulation control strategy has been incorporated using various energy storage systems (ESS) to established the frequency in interconnected power system. The supremacy of the proposed controller is established by comparing the system dynamic response with some existing controllers, such as proportional-integral-derivative (PID), tilt-integral-derivative (TID) and cascade of IDD - PID controllers. The fruitfulness of proposed AHA has also been evaluated with system dynamic and convergence characteristics comparison over some of existing metaheuristic optimization techniques such as harris hawk's optimization (HHO) and bird swarm algorithm (BSA). Further, effect of random load pattern (RLP), communication time delay (CTD) and variable CTD on the system dynamic is analyzed. The study of inertia emulation control strategy in a multi-area interconnected power system revealed that, when inertia is emulated with superconducting magnetic energy storage (SMES), the system dynamic exhibits better performance over battery energy storage (BES) and ultra-capacitor (UC). Furthermore, the proposed systems are validated in a real-time environment using OPAL-RT lab software. Also, the scalability of the proposed method is evaluated by using eigenvalue analysis.

0‐3 magnetic nanocomposites via EPD: Current status for power component fabrication and future directions

AbstractInductors and transformers (here referred to as power components) for modern AC/DC switching power supplies require magnetic materials that have high power density and efficiency at high frequencies, with high magnetic saturation, low coercivity, and multi‐micrometer thicknesses to increase magnetic energy storage and power handling. Rather than using a single‐phase magnetic material in a polymer‐based composite, a composite formed from two magnetic phases (such as a 0‐3 nanocomposite) can simultaneously achieve all of the listed requirements and benefit from contributions by both the zero‐ and three‐dimensional phases to the magnetic properties. The fabrication of 0‐3 magnetic nanocomposites for power component applications requires a method to deposit magnetic nanoparticles into thick, physically stable yet porous films, and a subsequent method for infiltrating the magnetic nanoparticle film with another magnetic material. Here, the deposition of magnetic nanoparticles into micron‐thick films using electrophoretic deposition (EPD) is discussed. This is described along with a new method, to improve upon traditional EPD methods by increasing film–substrate interactions with chelating agents, therefore increasing film stability. Next, the use of electro‐infiltration for fully incorporating a secondary magnetic material within the nanoparticle film is presented, showing the cumulative fabrication process with the addition of a multilayered nanocomposite fabrication technique for increasing overall nanocomposite thickness. The subsequent cross‐sectional and magnetic characterization of the fabricated 0‐3 nanocomposites is also shown. Finally, future directions for 0‐3 magnetic nanocomposites are offered, with emphasis on potential materials synthesis techniques and on translating knowledge beyond power component applications.

Application of COOT algorithm optimized PID plus D2 controller for combined control of frequency and voltage considering renewable energy sources

This article presents the combined frequency and voltage regulation of two area interconnected power systems. In addition to conventional generations, renewable energy sources such as wind plants, solar PV plants, and geothermal power plants are considered. The COOT algorithm optimized PID + D2 controller is presented for the first time and its performance found superior to commonly employed PI and PID controllers. The individual and combined effects of the boiler dynamics (BD) non-linearity and superconducting magnetic energy storage (SMES) systems are presented. Studies confirmed that the BD non-linearity jeopardizes, and the presence of SMES suppresses the system dynamics oscillations. The COOT based PID + D2 controller performs well even for the higher magnitudes of perturbations over the PID controller. Sensitivity analysis confirms the toughness of PID + D2 controller parameter values for widely varied time constants of the geothermal plant. The COOT algorithm optimized PID + D2 controller outperforms the PID controller in arbitrary load pattern perturbation. The COOT algorithm shows better convergence and figure of demerit characteristics compared with particle swarm optimization and firefly algorithms. The obtained simulation results are also tested successfully through OPAL-RT OP4500 RT-LAB-RCP/HIL system for their real-time validation.

Multi-area load frequency regulation of a stochastic renewable energy-based power system with SMES using enhanced-WOA-tuned PID controller

This paper presents a novel nature-inspired meta-heuristic optimization algorithm known as the Enhanced Whale Optimization Algorithm (EWOA), which imitates humpback whales' social behavior to solve the optimization of multi-area automatic load frequency control (LFC) problems of a stochastic renewable energy-based power system with superconducting magnetic energy storage (SMES). An EWOA algorithm is presented in response to the limitations of the conventional WOA algorithm, including its sluggish convergence time, low accuracy, and propensity to easily enter local optimum. The system model investigated includes some physical constraints such as the time delay (TD), generation rate constraint (GRC), reheat turbine (RT), and the dead band (DB). The impacts of these physical constraints on the dynamic performance of the proposed controller were investigated. The EWOA algorithm is utilized to dynamically optimize the parameters of the PID controller for optimal system performance. The effectiveness and dynamic performance of the proposed controller are compared with the conventional WOA using some performance metrics. The system model also includes superconducting magnetic energy storage (SMES) units in both areas and their impacts on the system performances are also investigated. The effects of the changes of two different parameters of the system (frequency bias parameter, B, and the governor speed regulation, R) on the frequency deviation responses and the controller's robustness are examined. It is evident from the results that the dynamic performance of the proposed controller is better than that of the conventional WOA and it is more robust and stable to changes in system loading, parameters, and step load perturbation.

Dynamic resistance loss of the high temperature superconducting coil for superconducting magnetic energy storage

The Superconducting Magnetic Energy Storage (SMES) has excellent performance in energy storage capacity, response speed and service time. Although it's typically unavoidable, SMES systems often have to carry DC transport current while being subjected to the external AC magnetic fields.Under this circumstance, the dynamic resistance loss occurs in conjunction with the magnetization loss. Accordingly, the dissipative heat originating from the dynamic resistance loss will cause thermal overhead and even threaten the stability of the SMES. To ensure the safe operation of the SMES, this study examines dynamic resistance losses of high temperature superconducting (HTS) coils. In addition, this study also compares it with other losses, including magnetization loss, under various conditions such as different DC transport currents, amplitudes, frequencies, and angles of external AC magnetic fields. Furthermore, the analysis of dynamic resistance loss has also taken into account thermal coupling. This research offers valuable insights into the electromagnetic-thermal characteristics of the HTS coil and can be used as a reference for designing SMES systems.

An effective SMES system control for enhancing the reliability of hybrid power generation systems

Recently, with the rising electrical energy demand, renewable energy resources (RERs) are considered an optimal solution for satisfying consumption needs. The power generated from RERs has an intermittent and unpredictable nature, given that it depends directly on weather conditions. Thus, the amount generated power from RERs will be taken in fluctuated curve form. This paper focuses on addressing the issue of fluctuation in the power output of a Solar-Wind hybrid power generation systems (HPGSs) resulting from variable weather conditions. Superconducting magnetic energy storage (SMES) system provide a viable solving to the issue of power output fluctuations in HPGSs due to their unique characteristics. To this aim, this paper proposes two robust controllers for SMES systems to smooth out the power provided by a HPGS. In order to evaluate the proposed SMES system efficiency's during significant and fast fluctuations (at level of up to ∼1 MW in the range and seconds in the duration), computer simulations were implemented using the MATLAB/Simulink software package. The results obtained from the simulations have confirmed that the controllers of the proposed SMES system could efficiently reduce power output fluctuations from HPGSs, minimize power losses on the transmission lines, and regulate the voltage at the point of common coupling (PCC) at an acceptable standard level.

A Measuring System for HTS Wires and Coils Properties at Low Temperatures

The use of high temperature superconducting materials (HTS) in various applications, requires knowledge of their critical parameters like critical current, critical magnetic field and critical temperature, in DC applications like high magnetic field generators, superconducting magnetic energy storage system (SMES), magnetic resonance imaging (MRI), magnets for particle accelerators, SC Maglev trains and other applications. Also, these parameters are important for specific properties in alternating current applications like fault current limiters, transformers, generators, motors, and power transmission lines. An important characteristic that needs to be tucked into consideration for AC applications is the power losses that occur in the HTS superconducting materials, which limits the maximum performance that the superconducting materials can attain for these applications. In order to measure these characteristics, which depend on the type of material used, but also on the temperature and other parameters, it is necessary to use an appropriate setup device that allows both obtaining the working temperature range (4.2 K to 300 K and other necessary parameters like high vacuum 10-6 mbar, high current supply (500 A), high magnetic field measurement system (1-10 T), etc. For the cryogenic cooling of the entire system, a closed cycle Gifford-McMahon type cryocooler is used, with two cooling stages, stage I at 50 K and second stage at 4.2 K (liquid Helium temperature). The set-up system used for measurement of the parameters of HTS superconducting materials (YBCO, BSCCO or MgB2) and the various coils made with them, is described in this article together with its functional parameters and some experimental results obtained by testing an YBCO coils system. The maximum generated magnetic flux density was 5 T in the centre of the coils system.

Technical challenges and optimization of superconducting magnetic energy storage in electrical power systems

The main motivation for the study of superconducting magnetic energy storage (SMES) integrated into the electrical power system (EPS) is the electrical utilities' concern with eliminating Power Quality (PQ) issues and greenhouse gas emissions. This article aims to provide a thorough analysis of the SMES interface, which is crucial to the EPS. This article also discusses the development of SMES as a reliable energy storage system (ESS). Delivering outstanding performance to support the EPS in any upsetting scenario can help SMES achieve its goals. A few of the fascinating aspects of the application of SMES in this context are microgrids, transmission and distribution (T&D) grids, renewable energy sources (RES), and plug-in hybrid energy storage systems (HESS). However, power utilities must evaluate the effectiveness and enhance a better performance on PQ when presenting a highly efficient energy technology. This article examines the difficulties of integrating SMES into the electricity network as well as the performance effects of HESS and RES. Finally, by outlining the current state of knowledge and highlighting any gaps in the literature, the power protection strategies and difficulties for power networks using SMES are evaluated.

Adaptive virtual inertia controller based on machine learning for superconducting magnetic energy storage for dynamic response enhanced

The goal of this paper was to create an adaptive virtual inertia controller (VIC) for superconducting magnetic energy storage (SMES). An adaptive virtual inertia controller is designed using an extreme learning machine (ELM). The test system is a 25-bus interconnected Java Indonesian power grid. Time domain simulation is used to evaluate the effectiveness of the proposed controller method. To simulate the case study, the MATLAB/Simulink environment is used. According to the simulation results, an extreme learning machine can be used to make the virtual inertia controller adaptable to system variation. It has also been discovered that designing virtual inertia based on an extreme learning machine not only makes the VIC adaptive to any change in the system but also provides better dynamics performance when compared to other scenarios (the overshoot value of adaptive VIC is less than -5×10-5).

Protection System Architecture for All-Electric Aircraft

To reduce emissions from the aviation industry and meet the targets set by different countries, research has been focused on investigating all-electric aircraft. To make this vision practical, superconducting machines are expected to power the propellers, as they are half the size and a third the weight of conventional machines. The main purpose of this paper is to do a higher-level study of a reliable holistic protection system for all-electric aircraft; that can reduce heat leakage and be able to detect faults reliably. Thus, three main protection systems were investigated; 1) cryogenic voltage source converter superconducting magnetic energy storage system (VSC-SMES), 2) cryogenic dc breaker integrated with superconducting fault current limiter (SFCL), and 3) machine learning algorithm for fault detection. By immersing the protection system at cryogenic temperature, the paper has shown that passive leakage can be eliminated, and thus more energy can be saved for the fuel cell. The paper has also demonstrated that using machine learning for the SFCL-dc-breaker system can consistently eliminate faults and protect the system.

Energy Storing and Fault Current Limiting in a Unified Superconducting Magnetic Device

This work describes a novel concept for unifying Superconducting Magnetic Energy Storage (SMES) and an inductive-type Fault Current Limiter (FCL). A single superconducting coil is used both as an energy source for the operation of the SMES and as the field source for saturating the magnetic cores in the FCL. A possible geometry model for the implementation of this concept is suggested and a test case in an 11 kV, 10 MVA network is described for a fully, and 50% charged SMES states. Results show that the Saturated Cores FCL exhibits low insertion impedance and high limiting ratio in both scenarios. The unified SMES-FCL device saves major resources by making the superconducting coil a dual-purpose source, thus opening the door for an easier and efficient implementation of SMES and FCL technologies.

Superconducting Magnetic Energy Storage for Pulsed Power Magnet Applications

As part of the exploration of energy efficient and versatile power sources for future pulsed field magnets of the National High Magnetic Field Laboratory-Pulsed Field Facility (NHMFL-PFF) at Los Alamos National Laboratory (LANL), the feasibility of superconducting magnetic energy storage (SMES) for pulsed-field magnets and other pulsed power loads is examined. Basic SMES parameters needed to power one of the coil groups of the large 100 T magnet were determined. A circuit topology for the power transfer between the SMES and the magnet was devised, and the basic performance of the topology was simulated to reproduce the pulse shape currently used in the 100 T magnet. The Finite element analysis (FEA) method was used to calculate the magnetic field distribution of several preferred coil configurations for effective SMES design. Magnetic field distribution and the field dependent critical current density of commercial high temperature superconducting (HTS) tapes were used to understand the conductor/cable requirements for the SMES.

Performance evaluation of microgrid with extreme learning machine based PID controller

The enhanced penetration of the renewable energy sources (RES) is dependent on microgrid (MG) to a power system is impact stability of the system due to a variation in dynamic properties of the MG from a traditional generator. As a result, analyzing the new issues with dynamic stability and controlling the operation of the power system in the connection of rising MG penetration becomes critical. This paper contains a MG system with renewable energy assisted, superconducting magnetic energy storage (SMES) storage and an extreme learning machine (ELM) based proportional integral derivative (PID) controller. The effect of renewable-based MG penetration on a dynamic stability and control of the multi machine multi area system under varied operating situations is comprehensively investigated in this study. Non-linear time-domain simulations and several performance indicators are used to evaluate the controller's ability with the different MG penetration percentages under various disturbances and operational conditions.

Performance evaluation of microgrid with extreme learning machine based PID controller

The enhanced penetration of the renewable energy sources (RES) is dependent on microgrid (MG) to a power system is impact stability of the system due to a variation in dynamic properties of the MG from a traditional generator. As a result, analyzing the new issues with dynamic stability and controlling the operation of the power system in the connection of rising MG penetration becomes critical. This paper contains a MG system with renewable energy assisted, superconducting magnetic energy storage (SMES) storage and an extreme learning machine (ELM) based proportional integral derivative (PID) controller. The effect of renewable-based MG penetration on a dynamic stability and control of the multi machine multi area system under varied operating situations is comprehensively investigated in this study. Non-linear time-domain simulations and several performance indicators are used to evaluate the controller's ability with the different MG penetration percentages under various disturbances and operational conditions.

Optimization of High Power SMES for Naval Applications

The electrification of transport has been no exception for waterborne vessels. The reduction of emissions, especially dur-ing port maneuvering and operation, has accelerated the transi-tion from fossil fuel to electric propulsion. Moreover, military ves-sels, with specialized electric weapon systems, or civil vessels, like offshore wind tug boats, have high power systems that additionally contribute to a higher electrification of the ship grid. Energy stor-age systems are essential to meet the power load economically and to improve the system`s reliability and efficiency. Therefore, the use of high energy density storage systems, as chemical batteries, or hydrogen fuel cells, has experienced a significant increase in de-mand. However, during high frequency load fluctuations, high en-ergy density storage systems are not capable to actuate, since the discharge rate of these systems is physically limited, which may provoke: deterioration and reduction of the lifetime of the storage systems, voltage and frequency fluctuation of the ship grid. To overcome this limitation, this paper studies the use of a Supercon-ducting Magnetic Energy Storage (SMES) as a supporting energy storage device for the ship grid. The guidelines for dimensioning, in power and energy, the SMES are stablished. Furthermore, an optimization method is developed in order to compare different superconducting materials, and operating temperatures.

Sudden Discharging Tests and Overcurrent Tests of a 3T HTS Model Magnet for MRI Systems Equipped With Electrically Conductive Epoxy Resin

A 3 T HTS MRI model magnet equipped with conductive epoxy resin for quench protection was designed and fabricated in 2021 and the REBCO multicoil generated 3 T with 143 A stably with no abnormal voltages. In this coil, the electrically conductive epoxy resin is attached to the edge of the winding as a bypass circuit between turns so that the excessive current can flow across turns in the radial direction to suppress local heat generation automatically. However, when the voltage of the coil rises as a start point in a quench protection process, the DC power supply is shut down by a quench detector and the magnet is suddenly discharged. Then, part of the magnetic stored energy is consumed in the coil and the coil temperature increases, which suggests the load factor increases during the sudden discharging operation. In this study, the sudden discharging tests were performed, and the behavior of the coil voltages and temperatures was evaluated at 30 K and 40 K using the middle-scale REBCO coil that had large inductance and high stored energy (3 T, 91 H, 1 MJ). After that, the overcurrent tests were performed for the verification of the quench protection at 50 K. The coil temperature reached 72 K at maximum, however, thermal runaway was avoided and the REBCO coil was protected.